Guiding Low Spatial Ability Individuals Through Visual Salience Cueing: The Dual Importance Of Where And When To Look
Notice bibliographique
Résumé
Background Research in education suggests that spatial ability may be a predictor of student success in spatially complex disciplines, including anatomy. Many anatomical structures and systems interact both functionally, and spatially within the human body, and as a result, mastery of anatomy requires a comprehensive understanding of these spatial relationships. Debate exists regarding the malleability of spatial ability, yet some researchers demonstrate that spatial ability can be enhanced through various training protocols, typically requiring long‐term experience. It is proposed that the ability of spatially low‐performing individuals can be trained in a brief period of time through visual guidance. Methods Training consisted of a visual guidance protocol based on the visual apprehension patterns of high spatial individuals during the completion of an electronic Mental Rotations Test (EMRT) based on the line drawings of Shepherd and Metzler. The effects of visual guidance were evaluated using 33 low spatial individuals, as classified by the Vandenberg and Kuse Mental Rotation test in a counterbalanced crossover design. (Mean score = 5.1 ± 1.9 (SD); Mean Age = 25.9± 5.0 yrs; n=33, 24F: 9M) Individuals in the treatment groups (Early, or Late Training) were exposed to both a guided electronic mental rotation test (EMRT) and an unguided EMRT, while control group participants completed the unguided EMRT twice. Results All groups demonstrated an increase in EMRT scores on their second iteration of the test (F2, 30) = 28.29 (p<0.001); however an interaction was observed between treatment group and test iteration F(2, 30) = 4.22 (p = 0.024). The effect of visual guidance on EMRT scores was contingent on when the visual guidance was applied. When guidance was applied at the outset of training, the observed increase in scores were significantly greater than that expected based on repetition alone (Early Guidance: 6.91 ± 2.46 (95% CI) vs. Late Guidance: 2.82 ± 1.69 and No Guidance: 3.55 ± 1.43) (t(10) = 2.58, p = 0.028). Analysis of agreement in salience patterns revealed that Late Guidance agreed with exemplars in 22% of question (κ = 0.11) on the Unguided EMRT, and 37% on the Guided EMRT (κ =0.25). Early Guidance agreed with exemplars on 22% of questions (κ = 0.11) on the Unguided EMRT, and 44% on the Guided EMRT (κ =0.33). Controls agreed on 44% and 25% of questions (κ = 0.33 and 0.09) on both Unguided EMRTs. Summary The current findings suggest that by guiding low spatial individuals “where” to look during spatial problem solving at the outset of training, better search approaches may be adopted and improvements in overall spatial reasoning may be observed. It is proposed that visual guidance derived from eye tracking may be translated to improvements in spatially complex domains such as STEMM (Science, Technology, Engineering, Mathematics and Medicine), surgery, aeronautics and anatomy. Support or Funding Information This research was conducted with support from the Social Sciences and Humanities Research Council of Canada.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».